SoroushVahidi/scidocs huggingface dataset:
Automatic C-to-CUDA Code Generation for Affine Programs
(2010)

Graphics Processing Units (GPUs) offer tremendous computational power. CUDA (Compute Unified Device Architecture) provides a multi-threaded parallel programming model, facilitating high performance implementations of general-purpose computations. However, the explicitly managed memory hierarchy and multi-level parallel view make manual development of high-performance CUDA code rather complicated. Hence the automatic transformation of sequential input programs into efficient parallel CUDA programs is of considerable interest. This paper describes an automatic code transformation system that generates parallel CUDA code from input sequential C code, for regular (affine) programs. Using and adapting publicly available tools that have made polyhedral compiler optimization practically effective, we develop a C-to-CUDA transformation system that generates two-level parallel CUDA code that is optimized for efficient data access. The performance of automatically generated code is compared with manually optimized CUDA code for a number of benchmarks. The performance of the automatically generated CUDA code is quite close to hand-optimized CUDA code and considerably better than the benchmarks’ performance on a multicore CPU.
An Experimental Evaluation of Apple Siri and Google Speech Recognition
(2015)

We perform an experimental evaluation of two popular cloud-based speech recognition systems. Cloudbased speech recognition systems enhances Web surfing, transportation, health care, etc. Using voice commands helps drivers stay connected to the Internet by avoiding traffic safety risks. The performance of these type of applications should be robust under difficult network conditions. User frustration with network traffic problems can affect the usability of these applications. We evaluate the performance of two popular cloud-based speech recognition applications, Apple Siri and Google Speech Recognition (GSR) under various network conditions. We evaluate transcription delay and accuracy of transcription of each application under different packet loss and jitter values. Results of our study show that performance of cloud-based speech recognition systems can be affected by jitter and packet loss; which are commonly occurring over WiFi and cellular network connections. keywords: Cloud Speech Recognition, Quality of Experience, Software Measurement, Streaming Media, Real-time Systems.
Interactive evolution for the procedural generation of tracks in a high-end racing game
(2011)

We present a framework for the procedural generation of tracks for a high-end car racing game (TORCS) using interactive evolution. The framework maintains multiple populations and allow users to work both on their own population (in single-user mode) or to collaborate with other users on a shared population. Our architecture comprises a web frontend and an evolutionary backend. The former manages the interaction with users (e.g., logs registered and anonymous users, collects evaluations, provides access to all the evolved populations) and maintains the database server that stores all the present/past populations. The latter runs all the tasks related to evolution (selection, recombination and mutation) and all the tasks related to the target racing game (e.g., the track generation). We performed two sets of experiments involving five human subjects to evolve racing tracks alone (in a single-user mode) or cooperatively. Our preliminary results on five human subjects show that, in all the experiments, there is an increase of users' satisfaction as the evolution proceeds. Users stated that they perceived improvements in the quality of the individuals between subsequent populations and that, at the end, the process produced interesting tracks.
Bandwidth-Enhanced Low-Profile Cavity-Backed Slot Antenna by Using Hybrid SIW Cavity Modes
(2012)

A bandwidth enhanced method of a low-profile substrate integrated waveguide (SIW) cavity-backed slot antenna is presented in this paper. Bandwidth enhancement is achieved by simultaneously exciting two hybrid modes in the SIW-backed cavity and merging them within the required frequency range. These two hybrid modes, whose dominant fields are located in different half parts of the SIW cavity, are two different combinations of the and resonances. This design method has been validated by experiments. Compared with those of a previously presented SIW cavity-backed slot antenna, fractional impedance bandwidth of the proposed antenna is enhanced from 1.4% to 6.3%, its gain and radiation efficiency are also slightly improved to 6.0 dBi and 90%, and its SIW cavity size is reduced about 30%. The proposed antenna exhibits low cross polarization level and high front to back ratio. It still retains advantages of low-profile, low fabrication cost, and easy integration with planar circuits.
Ontology semantic approach to extraction of knowledge from holy quran
(2013)

With the continued demand for Islamic knowledge, which is mainly based on the Quran as a source of knowledge and wisdom, systems that facilitate an easy search of the content of the Quran remain a considerable challenge. Although in recent years there have been tools for Quran search, most of these tools are based on keyword search, meaning that the user needs to know the correct keywords before being able to retrieve the content of al-Quran. In this paper, we propose a system that supports the end user in querying and exploring the Quran ontology. The system comprises user query reformulation against the Quran ontology stored and annotated in the knowledge base. The Quran ontology consists of noun concepts identified in al-Quran, and the relationship that exists between these concepts. The user writes a query in the natural language and the proposed system reformulates the query to match the content found in the knowledge base in order to retrieve the relevant answer. The answer is represented by the Quranic verse related to the user query.
A survey on text mining techniques
(2014)

text mining is a technique to find meaningful patterns from the available text documents. The pattern discovery from the text and document organization of document is a well-known problem in data mining. Analysis of text content and categorization of the documents is a complex task of data mining. In order to find an efficient and effective technique for text categorization, various techniques of text categorization and classification is recently developed. Some of them are supervised and some of them unsupervised manner of document arrangement. This presented paper discusses different method of text categorization and cluster analysis for text documents. In addition of that a new text mining technique is proposed for future implementation. Keywords— text mining, classification, cluster analysis, survey
Bullying among young adolescents: the strong, the weak, and the troubled.
(2003)

OBJECTIVES
Bullying and being bullied have been recognized as health problems for children because of their association with adjustment problems, including poor mental health and more extreme violent behavior. It is therefore important to understand how bullying and being bullied affect the well-being and adaptive functioning of youth. We sought to use multiple data sources to better understand the psychological and social problems exhibited by bullies, victims, and bully-victims.


DESIGN, SETTING, AND PARTICIPANTS
Analysis of data from a community sample of 1985 mostly Latino and black 6th graders from 11 schools in predominantly low socioeconomic status urban communities (with a 79% response rate).


MAIN OUTCOME MEASURES
Peer reports of who bullies and who is victimized, self-reports of psychological distress, and peer and teacher reports of a range of adjustment problems.


RESULTS
Twenty-two percent of the sample was classified as involved in bullying as perpetrators (7%), victims (9%), or both (6%). Compared with other students, these groups displayed school problems and difficulties getting along with classmates. Despite increased conduct problems, bullies were psychologically strongest and enjoyed high social standing among their classmates. In contrast, victims were emotionally distressed and socially marginalized among their classmates. Bully-victims were the most troubled group, displaying the highest level of conduct, school, and peer relationship problems.


CONCLUSIONS
To be able to intervene with bullying, it is important to recognize the unique problems of bullies, victims, and bully-victims. In addition to addressing these issues directly with their patients, pediatricians can recommend school-wide antibullying approaches that aim to change peer dynamics that support and maintain bullying.
The MagicBook - Moving Seamlessly between Reality and Virtuality
(2001)

or more than a decade researchers have tried to create intuitive computer interfaces by blending reality and virtual reality. The goal is for people to interact with the digital domain as easily as with the real world. Various approaches help us achieve this—in the area of tangible interfaces, we use real objects as interface widgets; in augmented reality, researchers overlay 3D virtual imagery onto the real world; and in VR interfaces , we entirely replace the real world with a computer generated environment. As Milgram pointed out, 1 these types of computer interfaces can be placed along a continuum according to how much of the user's environment is computer generated (Figure 1). Tangible interfaces lie far to the left on this reality–virtuality line, while immersive virtual environments are at the right extremity. Most current user interfaces exist as discrete points along this continuum. However, human activity can't always be broken into discrete components and for many tasks users may prefer to move seamlessly along the reality–virtuality continuum. This proves true when interacting with 3D graphical content, either creating virtual models or viewing them. For example, if people want to experience a virtual scene from different scales, then immer-sive virtual reality may be ideal. If they want to have a face-to-face discussion while viewing the virtual scene, an augmented reality interface may be best. 2 The MagicBook project is an early attempt to explore how we can use a physical object to smoothly transport users between reality and virtuality. Young children often fantasize about flying into the pages of a fairy tale and becoming part of the story. The MagicBook project makes this fantasy a reality using a normal book as the main interface object. People can turn the pages of the book, look at the pictures, and read the text without any additional technology (Figure 2a). However, if a person looks at the pages through an augmented reality display, they see 3D virtual models appearing out of the pages (Figure 2b). The models appear attached to the real page so users can see the augmented reality scene from any perspective by moving themselves or the book. The virtual content can be any size and is animated, so the augmented reality view is an enhanced version of a traditional 3D pop-up book. Users can change the virtual models by turning the book pages. When they see a scene they particularly like, …
Three stage 6–18 GHz high gain and high power amplifier based on GaN technology
(2010)

A monolithic three stage HPA has been developed for wide band applications. This MMIC is fabricated on UMS 0.25 µm GaN technology based on SiC substrate. At 18GHz, the MMIC achieved in CW mode 10W of output power with 20dB linear gain and 20% power added efficiency. The HPA provided 6 to 10W output power over 6 to 18GHz with minimum small signal gain of 18dB. These obtained performances are very promising and very close to the simulations; this will allow a very short term further improvement. This demonstration is the first MMIC on the UMS 0.25µm GaN technology.
Emotion regulation for frustrating driving contexts
(2011)

Driving is a challenging task because of the physical, attentional, and emotional demands. When drivers become frustrated by events their negative emotional state can escalate dangerously. This study examines behavioral and attitudinal effects of cognitively reframing frustrating events. Participants (N = 36) were asked to navigate a challenging driving course that included frustrating events such as long lights and being cut-off. Drivers were randomly assigned to three conditions. After encountering a frustrating event, drivers in a reappraisal-down condition heard voice prompts that reappraised the event in an effort to deflate negative reactions. Drivers in the second group, reappraisal-up, heard voice prompts that brought attention to the negative actions of vehicles and pedestrians. Drivers in a silent condition drove without hearing any voice prompts. Participants in the reappraisal-down condition had better driving behavior and reported less negative emotions than participants in the other conditions.
Facial Age Group Classification
(2014)

Estimating human age group automatically via facial image analysis has lots of potential real-world applications, such as human computer interaction and multimedia communication. However, It is still a challenging problem for the existing computer vision systems to automatically and effectively estimate human age group. The aging process is determined by not only the person’s gene, but also many external factors, such as health, living style, living location, and weather conditions. Males and females may also age differently. An age group classification system for facial images is proposed in this paper. Five age groups including babies, children, young adults, middle-aged adults, and old adults, are used in the classification system. The process of the system is divided into threephases: location, feature extraction, and age classification. Geometric features are used to distinguish whether the face is baby or child. Wrinkle features are used to classify the image into one of three adult groupsyoung adults, middle-aged adults, and old adults.
Reflections on craft: probing the creative process of everyday knitters
(2009)

Crafters today blend age-old techniques such as weaving and pottery with new information and communication technologies such as podcasts, online instructions, and blogs. This intersection of tradition and modernity provides an interesting site for understanding the adoption of new technology. We present a qualitative study of seven knitters introduced to Spyn - a system that enables the association of digitally recorded messages with physical locations on knit fabric. We gave knitters Spyn in order to elicit their reflections on their craft practices and learn from their interactions with material, people, and technology. While creating artifacts for friends and loved ones, knitters expanded the creative and communicative potential of their craftwork: knitters envisioned travel journals in knitted potholders and sung lullabies in knitted hats. We describe how these unusual craft activities provide a useful lens onto contemporary technological appropriation.
W-net: Bridged U-net for 2D Medical Image Segmentation
(2018)

In this paper, we focus on three problems in deep learning based medical image segmentation. Firstly, U-net, as a popular model for medical image segmentation, is difficult to train when convolutional layers increase even though a deeper network usually has a better generalization ability because of more learnable parameters. Secondly, the exponential ReLU (ELU), as an alternative of ReLU, is not much different from ReLU when the network of interest gets deep. Thirdly, the Dice loss, as one of the pervasive loss functions for medical image segmentation, is not effective when the prediction is close to ground truth and will cause oscillation during training. To address the aforementioned three problems, we propose and validate a deeper network that can fit medical image datasets that are usually small in the sample size. Meanwhile, we propose a new loss function to accelerate the learning process and a combination of different activation functions to improve the network performance. Our experimental results suggest that our network is comparable or superior to state-of-the-art methods.
Multimodal imaging of optic disc drusen.
(2013)

PURPOSE
To evaluate optic disc drusen, extracellular protein deposits known to contain numerous aggregates of mitochondria, using multimodal modalities featuring optical coherence tomography (OCT) and autofluorescence imaging.


DESIGN
Retrospective observational case series.


METHODS
Eyes with optic nerve drusen were examined with enhanced depth imaging (EDI)-OCT, swept source OCT, and fundus autofluorescence using a fundus camera.


RESULTS
Twenty-six eyes of 15 patients with optic disc drusen were evaluated. EDI-OCT and swept source OCT showed multiple optic disc drusen at different levels; most were located immediately anterior to the lamina cribrosa. The drusen were ovoid regions of lower reflectivity that were bordered by hyperreflective material, and in 12 eyes (46.2%) there were internal hyperreflective foci. The mean diameter of the optic disc drusen as measured in OCT images was 686.8 (standard deviation ± 395.2) μm. There was a significant negative correlation between the diameter of the optic disc drusen and the global retinal nerve fiber layer thickness (r = -0.61, P = .001). There was a significant negative correlation between proportion of the optic disc drusen area occupied by optic nerve drusen as detected by autofluorescence imaging and the global retinal nerve fiber layer thickness (r = -0.63, P = .001).


CONCLUSIONS
Deeper-penetration OCT imaging demonstrated the internal characteristics of optic disc drusen and their relationship with the lamina cribrosa in vivo. This study also showed that both the larger the drusen and the more area of the optic canal occupied by drusen, the greater the associated retinal nerve fiber layer abnormalities.
A Compact Fractal Loop Rectenna for RF Energy Harvesting
(2017)

This letter presents a compact fractal loop rectenna for RF energy harvesting at GSM1800 bands. First, a fractal loop antenna with novel in-loop ground-plane impedance matching is proposed for the rectenna design. Also, a high-efficiency rectifier is designed in the loop antenna to form a compact rectenna. Measured results show that an efficiency of 61% and an output dc voltage of 1.8 V have been achieved over 12-kΩ resistor for 10 μW/cm2 power density at 1.8 GHz. The rectenna is able to power up a battery-less LCD watch at a distance of 10 m from the cell tower. The proposed rectenna is compact, easy to fabricate, and useful for various energy harvesting applications.
Explore, Exploit or Listen: Combining Human Feedback and Policy Model to Speed up Deep Reinforcement Learning in 3D Worlds
(2017)

We describe a method to use discrete human feedback to enhance the performance of deep learning agents in virtual three-dimensional environments by extending deep-reinforcement learning to model the confidence and consistency of human feedback. This enables deep reinforcement learning algorithms to determine the most appropriate time to listen to the human feedback, exploit the current policy model, or explore the agent’s environment. Managing the trade-off between these three strategies allows DRL agents to be robust to inconsistent or intermittent human feedback. Through experimentation using a synthetic oracle, we show that our technique improves the training speed and overall performance of deep reinforcement learning in navigating three-dimensional environments using Minecraft. We further show that our technique is robust to highly innacurate human feedback and can also operate when no human feedback is given.
Making sense of implementation theories, models and frameworks
(2015)

BACKGROUND
Implementation science has progressed towards increased use of theoretical approaches to provide better understanding and explanation of how and why implementation succeeds or fails. The aim of this article is to propose a taxonomy that distinguishes between different categories of theories, models and frameworks in implementation science, to facilitate appropriate selection and application of relevant approaches in implementation research and practice and to foster cross-disciplinary dialogue among implementation researchers.


DISCUSSION
Theoretical approaches used in implementation science have three overarching aims: describing and/or guiding the process of translating research into practice (process models); understanding and/or explaining what influences implementation outcomes (determinant frameworks, classic theories, implementation theories); and evaluating implementation (evaluation frameworks). This article proposes five categories of theoretical approaches to achieve three overarching aims. These categories are not always recognized as separate types of approaches in the literature. While there is overlap between some of the theories, models and frameworks, awareness of the differences is important to facilitate the selection of relevant approaches. Most determinant frameworks provide limited "how-to" support for carrying out implementation endeavours since the determinants usually are too generic to provide sufficient detail for guiding an implementation process. And while the relevance of addressing barriers and enablers to translating research into practice is mentioned in many process models, these models do not identify or systematically structure specific determinants associated with implementation success. Furthermore, process models recognize a temporal sequence of implementation endeavours, whereas determinant frameworks do not explicitly take a process perspective of implementation.
Example-based video color grading
(2013)

In most professional cinema productions, the color palette of the movie is painstakingly adjusted by a team of skilled colorists -- through a process referred to as color grading -- to achieve a certain visual look. The time and expertise required to grade a video makes it difficult for amateurs to manipulate the colors of their own video clips. In this work, we present a method that allows a user to transfer the color palette of a model video clip to their own video sequence. We estimate a per-frame color transform that maps the color distributions in the input video sequence to that of the model video clip. Applying this transformation naively leads to artifacts such as bleeding and flickering. Instead, we propose a novel differential-geometry-based scheme that interpolates these transformations in a manner that minimizes their curvature, similarly to curvature flows. In addition, we automatically determine a set of keyframes that best represent this interpolated transformation curve, and can be used subsequently, to manually refine the color grade. We show how our method can successfully transfer color palettes between videos for a range of visual styles and a number of input video clips.
High Accuracy Optical Flow Estimation Based on a Theory for Warping
(2004)

We study an energy functional for computing optical flow that combines three assumptions: a brightness constancy assumption, a gradient constancy assumption, and a discontinuity-preserving spatio-temporal smoothness constraint. In order to allow for large displacements, linearisations in the two data terms are strictly avoided. We present a consistent numerical scheme based on two nested fixed point iterations. By proving that this scheme implements a coarse-to-fine warping strategy, we give a theoretical foundation for warping which has been used on a mainly experimental basis so far. Our evaluation demonstrates that the novel method gives significantly smaller angular errors than previous techniques for optical flow estimation. We show that it is fairly insensitive to parameter variations, and we demonstrate its excellent robustness under noise. In Proc. 8th European Conference on Computer Vision, Springer LNCS 3024, T. Pajdla and J. Matas (Eds.), vol. 4, pp. 25-36, Prague, Czech Republic, May 2004 c © Springer-Verlag Berlin Heidelberg 2004 Received The Longuet-Higgins Best Paper Award.